The doctor will polygraph you now: ethical concerns with AI for fact-checking patients
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arXiv
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| Autori principali: | , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| author | Anibal, James Gunkel, Jasmine Awan, Shaheen Huth, Hannah Nguyen, Hang Le, Tram Bélisle-Pipon, Jean-Christophe Boyer, Micah Hazen, Lindsey Consortium, Bridge2AI Voice Bensoussan, Yael Clifton, David Wood, Bradford |
| author_facet | Anibal, James Gunkel, Jasmine Awan, Shaheen Huth, Hannah Nguyen, Hang Le, Tram Bélisle-Pipon, Jean-Christophe Boyer, Micah Hazen, Lindsey Consortium, Bridge2AI Voice Bensoussan, Yael Clifton, David Wood, Bradford |
| contents | Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors which could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for fact-checking, particularly in cases where the data/models may contradict the patient. Additionally, this report simulated the misuse of a verification system using patient voice samples and identified a potential LLM bias against patient-reported information in favor of multi-dimensional data and the outputs of other AI methods (i.e., AI self-trust). Finally, recommendations were presented for mitigating the risk that AI verification methods will cause harm to patients or undermine the purpose of the healthcare system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07896 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The doctor will polygraph you now: ethical concerns with AI for fact-checking patients Anibal, James Gunkel, Jasmine Awan, Shaheen Huth, Hannah Nguyen, Hang Le, Tram Bélisle-Pipon, Jean-Christophe Boyer, Micah Hazen, Lindsey Consortium, Bridge2AI Voice Bensoussan, Yael Clifton, David Wood, Bradford Computers and Society Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors which could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for fact-checking, particularly in cases where the data/models may contradict the patient. Additionally, this report simulated the misuse of a verification system using patient voice samples and identified a potential LLM bias against patient-reported information in favor of multi-dimensional data and the outputs of other AI methods (i.e., AI self-trust). Finally, recommendations were presented for mitigating the risk that AI verification methods will cause harm to patients or undermine the purpose of the healthcare system. |
| title | The doctor will polygraph you now: ethical concerns with AI for fact-checking patients |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2408.07896 |